Optimal irrigation water allocation using a genetic algorithm under various weather conditions

Growing water scarcity, due to growing populations and varying natural conditions, puts pressure on irrigation systems, which often are the main consumptive water users. Therefore, water resources management to improve the allocation of limited water supplies is essential. In this study, a non-linear programming optimization model with an integrated soil/water balance is developed to determine the optimal reservoir release policies and the optimal cropping pattern around Doroudzan Dam in the South-West of Iran. The proposed model was solved using a genetic algorithm (GA). Four weather conditions were identified by combining the probability levels of rainfall, evapotranspiration and inflow. Moreover, two irrigation strategies, full irrigation and deficit irrigation were modeled under each weather condition. The results indicate that for all weather conditions the total farm income and the total cropped area under deficit irrigation were larger than those under full irrigation. In addition, our results show that when the weather conditions and the availability of water changes the optimal area under corn and sugar beet decreases sharply. In contrast, the change in area cropped with wheat is small. It is concluded that the optimization approach has been successfully applied to Doroudzan Dam region. Thus, decision makers and water authorities can use it as an effective tool for such large and complex irrigation planning problems

Scaling to generalize a single solution of Richards' equation for soil water redistribution

Using scaling methods, a single solution of Richards' equation (RE) will suffice for numerous specific cases of water flow in unsaturated soils. In this study, a new method is developed to scale RE for the soil water redistribution process. Two similarity conditions are required: similarity in the shape of the soil water content profiles as well as of the water flux density curves. An advantage of this method is that it is not restricted to a specific soil hydraulic model - hence, all such models can be applied to RE. To evaluate the proposed method, various soil textures and initial conditions were considered. After the RE was solved numerically using the HYDRUS-1D model, the solutions were scaled. The scaled soil water content profiles were nearly invariant for medium- and fine-textured soils when the soil profile was not deeply wetted. The textural range of the soils in which the similarity conditions are held decreases as the initial conditions deal with a deeply wetted profile. Thus, the scaling performance was poor in such a condition. This limitation was more pronounced in the coarse-textured soils. Based on the scaling method, a procedure is suggested by which the solution of RE for a specific case can be used to approximate solutions for many other cases. Such a procedure reduces complicated numerical calculations and provides additional opportunities for solving the highly nonlinear RE as in the case of unsaturated water flow in soils

Scaling to generalize a single solution of Richards' equation for soil water redistribution

Using scaling methods, a single solution of Richards' equation (RE) will suffice for numerous specific cases of water flow in unsaturated soils. In this study, a new method is developed to scale RE for the soil water redistribution process. Two similarity conditions are required: similarity in the shape of the soil water content profiles as well as of the water flux density curves. An advantage of this method is that it is not restricted to a specific soil hydraulic model - hence, all such models can be applied to RE. To evaluate the proposed method, various soil textures and initial conditions were considered. After the RE was solved numerically using the HYDRUS-1D model, the solutions were scaled. The scaled soil water content profiles were nearly invariant for medium- and fine-textured soils when the soil profile was not deeply wetted. The textural range of the soils in which the similarity conditions are held decreases as the initial conditions deal with a deeply wetted profile. Thus, the scaling performance was poor in such a condition. This limitation was more pronounced in the coarse-textured soils. Based on the scaling method, a procedure is suggested by which the solution of RE for a specific case can be used to approximate solutions for many other cases. Such a procedure reduces complicated numerical calculations and provides additional opportunities for solving the highly nonlinear RE as in the case of unsaturated water flow in soils

Assessing the available surface water resources of Torogh Dam for agricultural consumption-problems and solutions for future

Shortage of water resources in Iran especially the Mashad area is a very severe problem due to the prevailing condition of arid and semi-arid climate. Prolong droughts will affect the availability of water in Iran. Therefore Torogh Dam Watershed of Mashad has been studied. It is located in a semi arid zone of the southeast corner of Mashad city with a population of 2.5 million covering an area of 16400 km². Water scarcity is a major issue in the study area. About 40% of the surface water resources of Torogh Dam are used to irrigate agricultural land. Lack of precipitation and inefficient management of the irrigated water have caused the cultivated land not fully exploited. In summer water demand and water supply is not equal for irrigation because amount of water for irrigation is not sufficient. This Paper reviews current and future scenario, problems and solutions in sustaining water resources at the downstream of Torogh Dam for agricultural consumption for the centre of Khorasan Razavi County. Result of this review indicated that low efficiency of irrigation, lake on modern irrigation system and lack of participatory irrigation management are important factors for surface water resources management

Modeling daily stream flow using plant evapotranspiration method

In hydrological models, soil conservation services (SCS) are one of the most widely used procedures to calculate the curve number (CN) in rainfall run-off simulation. Recently, another new CN accounting procedure has been mentioned, namely the plant evapotranspiration (ET) method or simply known as the plant ET method. This method is embedded in the Soil and Water Assessment Tool (SWAT) model which has been developed for watersheds covered by shallow soils or soils with low storage characteristics. It uses antecedent climate and plant evapotranspiration for calculation of daily curve number. In this study, the same method had been used to simulate the daily stream flow for Roodan watershed located in the southern part of Iran. The watershed covers 10570 km2 and its climate is arid to semi-arid. The modeling process required data from digital elevation model (DEM), land use map, and soil map. It also required daily meteorological data which were collected from weather stations from 1988 to 2008. Other than that, the Sequential Uncertainty Fitting-2 (SUFI-2) algorithm was utilized for calibration and uncertainty analysis of daily stream flow. Criteria of modeling performance were determined through the Nash-Sutcliffe and coefficient of determination for calibration and validation. For calibration, the values were reported at 0.66 and 0.68 respectively and for validation; the values were 0.51 and 0.55. Moreover, percentiles of absolute error between observed and simulated data in calibration and validation period were calculated to be less than 21.78 and 6.37 (m3/s) for 95% of the data. The results were found to be satisfactory under the climatic conditions of the study area

Evaluation of the Performance of ClimGen and LARS-WG models in generating rainfall and temperature time series in rainfed research station of Sisab, Northern Khorasan

Introduction:Many existing results on water and agriculture researches require long-term statistical climate data, while practically; the available collected data in synoptic stations are quite short. Therefore, the required daily climate data should be generated based on the limited available data. For this purpose, weather generators can be used to enlarge the data length. Among the common weather generators, two models are more common: LARS-WG and ClimGen. Different studies have shown that these two models have different results in different regions and climates. Therefore, the output results of these two methods should be validated based on the climate and weather conditions of the study region. Materials and Methods:The Sisab station is 35 KM away from Bojnord city in Northern Khorasan. This station was established in 1366 and afterwards, the meteorological data including precipitation data are regularly collected. Geographical coordination of this station is 37º 25׳ N and 57º 38׳ E, and the elevation is 1359 meter. The climate in this region is dry and cold under Emberge and semi-dry under Demarton Methods. In this research, LARG-WG model, version 5.5, and ClimGen model, version 4.4, were used to generate 500 data sample for precipitation and temperature time series. The performance of these two models, were evaluated using RMSE, MAE, and CD over the 30 years collected data and their corresponding generated data. Also, to compare the statistical similarity of the generated data with the collected data, t-student, F, and X2 tests were used. With these tests, the similarity of 16 statistical characteristics of the generated data and the collected data has been investigated in the level of confidence 95%. Results and Discussion:This study showed that LARS-WG model can better generate precipitation data in terms of statistical error criteria. RMSE and MAE for the generated data by LAR-WG were less than ClimGen model while the CD value of LARS-WG was close to one. For the minimum and maximum temperature data there was no significant difference between the RMSE and CD values for the generated and collected data by these two methods, but the ClimGen was slightly more successful in generating temperature data. The X2 test results over seasonal distributions for length of dry and wet series showed that LARS-WG was more accurate than ClimGen.The comparison of LARS-WG and ClimGen models showed that LARS-WG model has a better performance in generating daily rainfall data in terms of frequency distribution. For monthly precipitation, generated data with ClimGen model were acceptable in level of confidence 95%, but even for monthly precipitation data, the LARS-WG model was more accurate. In terms of variance of daily and monthly precipitation data, both models had a poor performance.In terms of generating minimum and maximum daily and monthly temperature data, ClimGen model showed a better performance compared to the LARS-WG model. Again, both models showed a poor performance in terms of variance of daily and monthly temperature data, though LAR-WG was slightly better than ClimGen. For lengths of hot and frost spells, ClimGen was a better choice compared to LARS-WG. Conclusion:In this research, the performances of LARS-WG and ClimGen models were compared in terms of their capability of generating daily and monthly precipitation and temperature data for Sisab Station in Northern Khorasan. The results showed that for this station, LARS-WG model can better simulate precipitation data while ClimGen is a better choice for simulating temperature data. This research also showed that both models were not very successful in the sense of variances of the generated data compared to the other statistical characteristics such as the mean values, though the variance for monthly data was more acceptable than daily data

A global Budyko model to partition evaporation into interception and transpiration

Evaporation is a crucial flux in the hydrological cycle and links the water and energy balance of a catchment. The Budyko framework is often used to provide a first-order estimate of evaporation, as it is a straightforward model with only rainfall and potential evaporation as required input. Many researchers have improved the Budyko framework by including more physics and catchment characteristics in the original equation. However, the parameterization of these improved Budyko models is not so straightforward, is data demanding, and requires local knowledge that is difficult to obtain at the global scale. In this paper we present an improvement of the previously presented Gerrits' model ("Analytical derivation of the Budyko curve based on rainfall characteristics and a simple evaporation model" in Gerrits et al., 2009 WRR), whereby total evaporation is calculated on the basis of simple interception and transpiration thresholds in combination with measurable parameters like rainfall dynamics and storage availability from remotely sensed data sources. While Gerrits' model was previously investigated for 10 catchments with different climate conditions and where some parameters were assumed to be constant, in this study we applied the model at the global scale and fed the model with remotely sensed input data. The output of the model has been compared to two complex land-surface models, STEAM and GLEAM, as well as the database of Landflux-EVAL. Our results show that total evaporation estimated by Gerrits' model is in good agreement with Landflux-EVAL, STEAM, and GLEAM. The results also show that Gerrits' model underestimates interception in comparison to STEAM and overestimates it in comparison to GLEAM, whereas the opposite is found for transpiration. Errors in interception can partly be explained by differences in the definition of interception that successively introduce errors in the calculation of transpiration. Relating to the Budyko framework, the model shows a reasonable performance for the estimation of total evaporation. The results also found a unimodal distribution of the transpiration to precipitation fraction (Et/p), indicating that both increasing and decreasing aridity will result in a decline in the fraction of transpired rainfall by plants for growth and metabolism.Water Resource

Data underlying the publication: A global Budyko model to partition evaporation into interception and transpiration

This model calculates total evaporation on the basis of simple interception and transpiration thresholds in combination with measurable parameters like rainfall dynamics and storage availability from remotely sensed data sources